CHICAGO (GenomeWeb) – With all the talk about how blockchain technology might finally represent the breakthrough in interoperability and security that precision medicine needs, actual usage of blockchain in life sciences research and clinical practice so far has been hard to find.

"It is more of a potential," said Kamaljit Behera, an industry analyst in the Visionary Healthcare Program at consulting and research firm Frost & Sullivan. Some pharmaceutical and medical device companies have completed proof-of-concept studies of blockchain technology, but as far as Behara knows, nothing has been commercialized yet.

Estonia has applied blockchain to 1 million health records to prevent a recurrence of a cyberattack that shut down that country's data systems for several days in 2007, according to Dutch blockchain software company Guardtime.

"Although 100 percent crime prevention is impossible, it is now possible to have 100 percent detection, accountability, and auditability across highly complex systems," Guardtime CEO Mike Gault wrote recently in a blog post on the firm's website.

But the Estonia example is an outlier, and it did not involve precision medicine.

When asked if he had seen blockchain-based applications for genomics in true research or clinical environments, physician Ron Ribitzky, a consultant in precision medicine and health informatics, said he hadn't, noting that the technology largely represents a lot of potential in healthcare.

One startup called Genecoin promises secure, perpetual backups of DNA sequences across the Bitcoin cryptocurrency network. If that sounds like a pie-in-the-sky idea, it may be just that. Genecoin actually suggested on its website that people create their own alternative currencies of sorts to store and share their own genomic data.

That is similar to the model that purveyors of consumer-controlled personal health records have put forth for two decades. To this day, not a single PHR brand has gained wide acceptance unless it is tightly linked to an institution's electronic health record.

"Technology, to date, hasn't been able to support a 'patient-first' approach," noted Emily Vaughn, head of accounts at enterprise blockchain company Gem.

Genecoin had a bit of a publicity blitz in late 2014. There was plenty of online skepticism then, and the company has been rather quiet ever since. Nobody from Genecoin responded to an emailed request for an interview for this article.

"Genecoin is one of those companies that went out there in the wild," he said. According to Ribitzky, the startup is on kind of a frontier expedition.

The same might be said of other blockchain developers in life sciences. "[The technology] does exist in the lab, but it's experimental," Ribitzky said.

A Russian startup called Zenome.io also is looking to put consumers in control of their genomic data, though cofounder Alexey Gorbachev called his company's nascent platform a "hybrid." The blockchain-based, peer-to-peer technology will automate collection and sharing of genomic data in part by allowing individuals to upload their own DNA profiles control which researchers may access and add to each secure store of information.

"It is for private storage of medical and genetic data," Gorbachev, a microbiologist explained. He called the system a "platform for buying and selling genomic data" for purposes including drug development and personalized medicine.

Users "can share it with each other and there will be privacy," added the other cofounder, Nikolay Kulemin, a bioinformaticist at the Research Institute for Physico-Chemical Medicine in Moscow. Indeed, sharing and privacy are two basic premises of blockchain.

Another idea being tested now is by Portland, Oregon-based startup Healthcoin, which aims to support employer and insurer wellness programs by rewarding healthy behaviors through the use of biomarkers from blood tests — hemoglobin A1c, HDL cholesterol, and blood pressure — rather than adjunct metrics like steps and other physical activity, with the goal of preventing diabetes.

Healthcoin relies on a blockchain to verify user identities and allow individuals to share their data with any trusted third party after running their records through an analytics engine.

EncrypGen, a startup from Coral Springs, Florida, launched in May at the annual Bio-IT World conference in Boston. That company is getting ready to beta test a blockchain-based system to allow patients to store and share genomic data through what it calls a "gene-chain."

And earlier this month, Insilico Medicine, which makes artificial intelligence software for genomics, entered into a partnership with blockchain technology developer the Bitfury Group. The companies will co-develop blockchain- and AI-based products to help academic researchers and drug companies discover and apply biomarkers for aging and age-related diseases.

Blockchain will help the three-year-old company better secure data to build trust among researchers and consumers alike, according to Zhu. "We are not an expert in blockchain, but Bitfury is."

In addition to the technology the company provides to academia and pharma, Insilico hosts two consumer-facing websites, Aging.ai and Young.ai. The former predicts biological age based on an analysis of dozens of biomarkers, while the latter seeks to prevent age-related disease through behavioral change.

Given that the deal was announced so recently, Bitfury is just getting started moving Insilico's software to a blockchain platform. "In the future, we want to integrate this technology into patient data" for both clinical trials and medical practice, Zhu said. In this scenario, blockchain would help with connectivity as well as security, he noted.

Meanwhile, a San Francisco-based startup named Doc.ai emerged from stealth mode last week by introducing a natural-language processing platform for quantified biology that relies on blockchain to, as the company said, "decentralize" artificial intelligence. To beta test its first module, called Robo-Hematology, Doc.ai chose Deloitte Life Sciences and Healthcare.

Alas, both Healthcoin and EncrypGen rely on patient control, a model that likely won't succeed unless EHR, laboratory, and genomic data all easily feed into their systems. And, like Healthcoin, Bitfury talked of "potential," not concrete results, while Doc.ai simply discussed a vision.

Doc.ai Cofounder and CEO Walter De Brouwer knows that nothing is a sure thing in the world of healthtech. Late last year, shortly after De Brouwer left his previous startup, Scanadu, that company pulled the plug on its widely hyped Scout diagnostic device when it became apparent that the US Food and Drug Administration would not clear the product.

Scanadu invented Scout for the Qualcomm Tricorder X Prize competition, a $10 million challenge to develop a handheld device to measure vital signs and diagnose common medical conditions, much like the fictional Tricorder on the original "Star Trek" series. But the abrupt shutdown caused a number of Indiegogo backers of Scanadu to call the product a "scam" and a "fraud," according to online news site Stat.

Regardless, some technologies that fail to live up to initial hype do eventually mature. That may be happening with blockchain in life sciences, but patience is paramount.

After all, a 1991 Institute of Medicine report suggested it could take 10 years for EHRs to become the norm in US healthcare. It took a quarter century for EHRs to replace most of the paper, though systems still aren't easy to use or widely interoperable.

For the near term — through 2018 — expect to see "some initial commercialization" of healthcare blockchain products, according to Frost & Sullivan's Behara. Imminently available applications should include digital identity verification and management, as well as drug supply-chain management.

In a few years, Behara foresees data exchange and e-consenting for clinical trials, while the longer-term future of blockchain promises regulatory audit trails, monitoring of adverse events, and management of universal health records.

The Human Gene Mutation Database (HGMD) is a manually curated, comprehensive collection of disease-causing, germline mutations. Since 1996, a team of experts has manually catalogued over a quarter of a million mutations for the database.